AIMC Topic: Risk Assessment

Clear Filters Showing 991 to 1000 of 2930 articles

NLP-based ergonomics MSD risk root cause analysis and risk controls recommendation.

Ergonomics
An ergonomics assessment of the physical risk factors in the workplace is instrumental in predicting and preventing musculoskeletal disorders (MSDs). Using Artificial Intelligence (AI) has become increasingly popular for ergonomics assessments becaus...

Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting.

Journal of the American Heart Association
BACKGROUND: Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision-making but remain limited. We developed machine learning algorithms that predict 1-year stroke o...

An artificial intelligence tool to assess the risk of severe mental distress among college students in terms of demographics, eating habits, lifestyles, and sport habits: an externally validated study using machine learning.

BMC psychiatry
BACKGROUND: Precisely estimating the probability of mental health challenges among college students is pivotal for facilitating timely intervention and preventative measures. However, to date, no specific artificial intelligence (AI) models have been...

Deciphering geochemical fingerprints and health implications of groundwater fluoride contamination in mica mining regions using machine learning tactics.

Environmental geochemistry and health
The contribution of mica mining activities to fluoride (F) contamination in groundwater has been chased in this study. For the purpose, groundwater samples (n = 40, replicated thrice) were collected during the post-monsoons (September-October) from a...

Identification and evaluation of deep foundation pit construction risks based on Grey-DEMATEL-Fuzzy comprehensive evaluation method.

PloS one
In recent years, foundation pit construction has been rapidly developing in the direction of deep and large-scale, leading to the frequent occurrence of construction accidents. The pit construction process is characterised by a complex environment, h...

Clinical Applications of Artificial Intelligence in Occupational Health: A Systematic Literature Review.

Journal of occupational and environmental medicine
OBJECTIVES: The aims of the study are to identify and to critically analyze studies using artificial intelligence (AI) in occupational health.

A stacking ensemble machine learning model for evaluating cardiac toxicity of drugs based on in silico biomarkers.

CPT: pharmacometrics & systems pharmacology
This study addresses the critical issue of drug-induced torsades de pointes (TdP) risk assessment, a vital aspect of new drug development due to its association with arrhythmia and sudden cardiac death. Existing methodologies, particularly those reli...

Precise management and control around the landfill integrating artificial intelligence and groundwater pollution risks.

Chemosphere
The Landfill plays an important role in urban development and waste disposal. However, landfill leachate may also bring more serious pollution and health risks to the surrounding groundwater environment. Compared with other areas, the area around the...

Artificial intelligence-based model for the recurrence of hepatocellular carcinoma after liver transplantation.

Surgery
BACKGROUND: Artificial intelligence-based models might improve patient selection for liver transplantation in hepatocellular carcinoma. The objective of the current study was to develop artificial intelligence-based deep learning models and determine...

Artificial intelligence-based data extraction for next generation risk assessment: Is fine-tuning of a large language model worth the effort?

Toxicology
To underpin scientific evaluations of chemical risks, agencies such as the European Food Safety Authority (EFSA) heavily rely on the outcome of systematic reviews, which currently require extensive manual effort. One specific challenge constitutes th...